jobd
A self-hostable, GPU-aware job broker for your own machines — with native MCP/agent integration.
Like task-spooler or pueue, but across all your machines — and VRAM-aware.
Demo recorded on jobd v0.5.30; output on later versions may differ.
You have a couple of boxes with GPUs — a workstation, a server, maybe a laptop — wired together over Tailscale or a LAN. You want to fire off training runs, data pipelines, and long batch jobs from anywhere, have them land on whichever machine actually has the VRAM free, survive across sessions, and get preempted cleanly when something more important shows up. You don't have a cloud, a Kubernetes cluster, or a Slurm install, and you don't want one.
jobd is that missing piece: a lightweight, single-process broker that turns a handful of personal machines into a single queue — and an LLM agent can drive it directly.
# from any machine on your tailnet:
job submit --project myproj --gpu --vram-required 16 --wait -- python train.py
# → routed to whichever worker has ≥16 GB VRAM free, streamed back to your terminal
